agents

#| standalone: true
#| viewerHeight: 620
#| components: [ viewer]
## file: wealth.py

import micropip
async def install_agentpy():    
    await micropip.install("agentpy")
install_agentpy()
#package_list = micropip.list()
#print(package_list)
import agentpy as ap

# Model design
class WealthAgent(ap.Agent):
    """ An agent with wealth """
    def setup(self):
        self.wealth = 1

    def wealth_transfer(self):
        if self.wealth > 0:
            partner = self.model.agents.random()
            partner.wealth += 1
            self.wealth -= 1

def gini(x):
    """ Calculate Gini Coefficient """
    x = np.array(x)
    mad = np.abs(np.subtract.outer(x, x)).mean()  # Mean absolute difference
    rmad = mad / np.mean(x)  # Relative mean absolute difference
    return 0.5 * rmad

class WealthModel(ap.Model):
    """ A simple model of random wealth transfers """
    def setup(self):
        self.agents = ap.AgentList(self, self.p.agents, WealthAgent)
    def step(self):
        self.agents.wealth_transfer()
    def update(self):
        self.record('Gini Coefficient', gini(self.agents.wealth))
    def end(self):
        self.agents.record('wealth')

## file: app.py
from wealth import *
from shiny.express import input, render, ui
from shinywidgets import render_widget


with ui.sidebar():    
    ui.panel_title("Hello Shiny!")
    ui.input_slider("n", "N", 0, 100, 20)
    ui.input_slider("agents", "Agents", 0, 100, 100),
    ui.input_slider("steps", "Steps", 0, 100, 100),
    ui.input_slider("x", "y", 0, 10, 10),
    ui.input_slider("y", "y", 0, 10, 10),
    ui.input_selectize(
        "var", "Select variable",
        choices=["bill_length_mm", "body_mass_g"]
    )

@render.text
def wealth_run():
    model = WealthModel(parameters)
    results = model.run()
    return f"{results.info['completed_steps']}"



@render.text
def txt():
    return f"n*2 is {input.n() * 2}"

@render.plot
def hist():
    from matplotlib import pyplot as plt
    from palmerpenguins import load_penguins

    df = load_penguins()
    df[input.var()].hist(grid=False)
    plt.xlabel(input.var())
    plt.ylabel("count")

## file: requirements.txt
pandas

## file: fruit.csv
id,name,count
1,"apple",20
2,"orange",12
3,"grape",100